Remote - Experimentation Data Scientist

Being good neighbors - helping people, investing in our communities, and making the world a better place - is who we are at State Farm. It is at the core of how we operate and the reason for our success. Come join a #1 team and do some good!

A Day in the Life of a Data Scientist at State Farm:

As a data scientist on the Enterprise Experimentation Team, you will help business partners examine new ideas by formulating hypotheses and designing experiments to test those hypotheses, allowing them to accurately and confidently quantify the impact of their strategic decisions. You will serve not just as a subject matter expert and consultant, but also as a teacher. Through this role, you will work to educate others on experimentation and grow the knowledge base of experimentation across the company.

Why Join Our Team:

Being on the Enterprise Experimentation Team will help promote your professional growth across multiple areas. First, you will enhance your business acumen by collaborating with a variety of business areas across the Enterprise to produce designed experiments and actionable results. Second, you will enrich your technical skills by facing challenges that require you to dig into your analytic toolbox to identify the right solution. Finally, you will strengthen your communication skills through interactions with business partners that require you to articulate statistical concepts in non-technical ways.

The Selection Process:

1. After submitting your application, our recruitment team will carefully review your qualifications. If your profile aligns with our requirements, you may progress to the next stage of the selection process.

2. The initial assessment will involve a video interview. This assessment will give you the opportunity to introduce yourself to them and showcase data science fundamental skill with some technical questions. Once you have completed and submitted the video interview our data science leadership will evaluate your responses.

3. If selected to move forward, you will have the opportunity to participate in a live video interview with members of our Hiring Team. This interview will provide a chance for us to further assess your technical expertise and suitability for the role.

4. Following the successful completion of the Hiring Team round, competitive candidates may be invited to the final stage of the process: a final loop interview. This round will involve interviews with members of our hiring panel, allowing us to gain deeper insights into your skills, and experiences.

In this role, you will share your knowledge and work to increase the use of Experimentation for decision making across the Enterprise. Below are some of the tasks you can expect in the typical day of a data scientist:

• Develop and validate advanced analytic models, designed experiments, and other data-driven solutions
• Provide input into and/or build datasets to support solution development
• Collaborate with other team members on scoping solutions and project decision points
• Present on technical topics to peers, leadership, and other stakeholders, including non-technical business partners
• Lead/mentor other data scientists, interns, and other technical work teams
• Make strategic recommendations on data collection, integration, and retention requirements, incorporating business requirements and knowledge of best practices
• Serve as a peer reviewer to other model development teams
• Establish and leverage a network of associates with business domain and data expertise
• Instill a business-oriented mindset that delivers business outcomes for State Farm's AI/ML portfolio

• Completed Masters, other advanced degrees, in an analytical field such as statistics, quantitative marketing, experimental psychology, operations research, management science, industrial engineering, etc., with 3+ years of predictive model building experience
• Practical work experience with, and understanding of, topics associated with A/B testing and other experimental design concepts for business contexts
• Ability to communicate basic statistical concepts (e.g., statistical significance, confidence intervals, regression models) to business partners
• Experience building advanced analytic solutions using generalized linear models and at least one of the following: time series analysis, cluster analysis, tree-based algorithms, or neural networks
• Experience with at least one statistical programming language: Python, R, or SAS

Other Things We Look For:

• Experience with mixed linear & non-linear model methodologies
• Experience with statistics-based experimental designs, causal inference, or difference-in-difference based estimation
• Experience with cloud-based environments (e.g., AWS) or Linux
• Strong communication skills and the ability to manage multiple, diverse stakeholders across business areas and leadership levels
• Experience gathering and interpreting business requirements for designing scalable data science solutions in a regulatory environment (e.g., insurance, healthcare, and finance).

PI259740879